Calorie Counting Using Pedometers


Pedometers can be beneficial in increasing physical activity by providing real-time feedback to users. Step count, distance traveled, and calories burned are often recorded by pedometers, allowing users to set the fitness goals and see if they are achieving them. Accelerometer pedometers are shown to be more accurate in counting steps than traditional mechanical pedometers, Distance traveled is based on the stride length of the user and step count, which can be calculated using the data collected by the pedometer. Some pedometers also provide a number for calories burned, but how accurate is this value and how is it calculated? The accuracy of this quantity may be beneficial for users who are basing their daily caloric intake on the amount of calories they believe they have burned. The current formula used to determine calories burned is: total calories burned = Duration (in minutes)*(MET*0.0175*weight in kg). MET is a value based on the intensity of the exercise being performed, as can be seen in the chart depicted on the Hospital for Special Surgery website [1]. How to accurately measure calories burned using a pedometer has not been determined. Heart rate can be a good way to determine intensity of exercise but not all pedometers include heart rate monitors. Some pedometers use the calculated speed of the user and their weight to estimate calories burned [2]. Studies have shown that calories burned is often underestimated when using a pedometer. Compared to metabolic data collected during exercise from VO2, the pedometer calorie count, that utilized weight, number of steps, stride length, and speed of the user, was lower [3]. The solution I propose is to implement a peak detection system that takes into account the amplitude of the acceleration waveform to correlate this to METs and calories burned. 



Most accelerometer pedometers utilize an adaptive peak detection system to distinguish extraneous movements from steps. A peak detection system is implemented to determine if a peak in the acceleration waveform should actually count as a step. An amplitude for the peak and a time threshold for the wave are used to determine if the movement qualifies as a step. When the required conditions are met, the step is counted and the system begins to search for the next peak in the acceleration data [4]. However, other than determining if the threshold value is met, the amplitude of the peak is not utilized. I propose that using the amplitude could provide a more accurate way of determining the intensity of the movement and could be applied to the calculation of calories burned. Although this will not be completely accurate, I believe that this would improve on the current method used in some pedometers to calculate calories burned. Pedometers that have heart rate monitors can use this data to more accurately predict energy expenditure but pedometers that do not often use crude calculations such as calories/kg/hr = 1.25 x speed (km/h) or calories/hr = 1 x weight (kg) while resting [2]. If the amplitude data can be stored and processed, this information could be correlated to METs, which may improve accuracy in energy expenditure data. 

Figure 1. Sample magnitude values that are found using data collected from the x, y, and z axis of the accelerometer during movement.[5]


In order to implement the peak magnitude system, the magnitude of all 3 axes could be found prior to filtering. Using the equation mag = sqrt(x^2+y^2+z^2), the overall magnitude of acceleration could be found for each movement. This data can then be filtered and smoothed returning a similar pattern as seen in figure 1 [5]. A peak detection system functions by analyzing time periods and determining where the peak falls within that interval. When a peak is detected that fulfills the magnitude threshold and time threshold, the pedometer tracks a step. If the magnitude of the peak can be stored, this could be used to determine the MET value of an activity. METs range from 1 – 23, 1 occurring when you are sitting at rest and 23 occurring during extremely vigorous exercise, such as running at a 4:30 mile pace [6].

Figure 2. Sample block diagram created in Simulink that could be used to calculate calories burned based on assigned MET values relating to different magnitudes of acceleration.

A block diagram, as seen in figure 2, could be used to correlate the magnitude to the intensity of exercise. This potential solution to the inaccuracies of energy expenditure calculated by pedometers still has some limitations. One limitation being that not all intense exercises will generate high acceleration values despite the large caloric expenditure. For example, squatting a one rep max may require a great deal of energy, but the pedometer may not pick it up as movement and therefore would not count it as a step. This is an example of where heart rate monitors may be beneficial in determining energy expenditure. Similarly, exercising on a stationary bike may be very intense but not trigger any steps to be counted if the pedometer is worn on the wrist and therefore would not be counted in the overall calorie burn for the user. This assumption that acceleration correlates directly to exercise intensity may accurately apply in all cases, but it could still improve the overall calculation of calories burned.    



  1. Women’s Sports Medicine Center, Hospital for Surgery. (2009). Burning Calories with Exercise: Calculating Estimated Energy Expenditure. Retrieved from
  2. Zhao, N. (2010). Full-Featured Pedometer Design Realized with 3-Axis Digital Accelerometer. Analog Dialogue, 44(6)
  3. Smith, K., Egercic, L., Bramble, A., Secich, J. (2017) Reliability and validity of the Omron HJ-720 ITC pedometer when worn at four different locations on the body, Cogent Medicine, 4:1
  4. Ravindran, S. (2013). US Patent No. US 2013/0191069A1. Retrieved from
  5. Alabadleh, Ahmad & Hawari, Eshraq & Alkafaween, Esra’a & Alsawalqah, Hamad. (2017). Step Detection Algorithm For Accurate Distance Estimation Using Dynamic Step Length. 324-327.
  6. Mcall, P. (2017). 5 Things to Know About Metabolic Equivalents. Retrieved from

How Wrist Pedometers Count Steps

Patent title: Adaptive Step Detection

Patent number: US 20130191069A1

Patent filing date: 01/18/2013

Patent issue date: 07/25/2013

Time it took for the patent to be issued: Just over 6 months

Inventor: Sourabh Ravindran

Assignee: Texas Instruments Incorporated

U.S. classification: G01C22/006 Pedometers

Number of claims: 7


Today, there are many different types of pedometers that are used by athletes and non-athletes alike. Brands such as Garmin, Fitbit, and Apple make smart watches that allow users to track their steps, distance covered, and floors climbed all while reading text messages and playing music. However, before these complex devices, people still used pedometers to track their steps. Traditional pedometers were worn on clipped to the waist and tracked steps based on the movement of the hips. This patent was filed by Texas Instruments Incorporated for a pedometer that would be worn on the wrist instead of the hip. Devices like this helped pave the way for the popular smart watches worn today. 

The main claim of this pedometer is that it can be worn on the wrist and can track steps as accurately as traditional pedometers worn on the hip (figure 1). The another main claim of this device is that it uses three accelerometers to track step data to account for sway and extraneous movements of the arm during daily life. The device also has the capacity to store data, which can be exported to other devices, such as a computer via USB or Bluetooth. In addition, the device has a screen to display step count or distance traveled. 

Figure 1. The design drawing of the wrist pedometer (600). 514 indicates the screen that will display the users step count, the distance traveled, or the time. 516 indicates a button that can be used to select what is displayed on the screen.

Traditional pedometers were worn on the belt and steps were detected based on the motion of the hips. Movement at the wrist is more complex and can result in more false steps than pedometers worn on the hip. The algorithm used to determine what is registered as a step was altered to account for this more complex motion. To do this, a three axis accelerometer was used to make motion detectable regardless of how the arm was oriented. Data from each axis is filtered and combined by summing the absolute value of each sample. The result is one graph that represents all of the acceleration data in order to get a more accurate depiction of when steps were taken (figure 2).


Figure 2. The graph of the combined waveform data from each of the three (x, y, and z) accelerometers. 322 and 323 indicate regions around inflection points, 330 points out a region where the amplitude of the slope exceeds the allowable threshold, 331 indicates the time duration of the positive slope region, and 333 indicates where the time threshold was exceeded for an inflection point region. When each threshold value is met, a step is registered for that particular sloping region.

 Using this plot, an adaptive peak detector is utilized in the hardware to quantify the acceleration of each movement. This detector identifies inflection points in the acceleration data collected to identify positive and negative slopes in the accelerations. If the slope regions reach or surpass a threshold value and last for a specified time threshold, then the device registers this as a step. The time restraint helps separate noise from actual step data. The detector then repeats this to track steps over time. Step frequency and the height of the user are determined in order to estimate stride length so that distance covered can also be output to the user. A study conducted showed that this device on the wrist is just as accurate as an older pedometer that was worn on the hip. 

Though the mechanisms used to count steps seem rather complex, this device could be used by anyone looking to track their daily steps. This device does not require any difficult training to use so learning how to use the device should not be a limiting factor for this device. Pedometers are used by people of all athletic abilities. If someone wants to begin exercising, this device could be used to track the number of steps accumulated during the day or during a particular workout. An avid runner could use this device to track the distance covered during a run based on stride length and step count. Therefore, this device can be widely used and may be of benefit to anyone trying to increase their physical fitness. Current wrist pedometers have exceeded the functions of this device, incorporating heart rate monitors, swim tracking, GPS tracking, and other technologies. The patent described some of these functions as potential future adaptations/embodiment of this device.



Ravindran, S. (2013). US Patent No. US 2013/0191069A1. Retrieved from

Elevation Masks for Endurance Training: Stamina or Scam?

Endurance athletes across the globe are always looking for a way to gain an edge on their opponents. Some methods that have been adopted by elite and amateur athletes alike are altitude and respiratory muscle training. Altitude training involves training at high altitudes where oxygen is more limited than at sea level. Respiratory muscle training involves strengthening the muscles that are required for breathing. Both types of training involve creating a hypoxic condition for the body, meaning that the tissues are not receiving an adequate supply of oxygen. Exposure to hypoxic conditions stimulates the production of erythropoietin in the kidneys, which increases production of red blood cells. This creates an increase in the oxygen carrying capacity of the blood and has been correlated to an increase in endurance performance [1].These training techniques are said to increase aerobic capacity (VO2max), endurance, lung function, and overall performance in athletes [2]. 

Respiratory muscle training can be done using an elevation mask, which is designed to simulate the conditions of training at altitude while training at sea level (figure 1). Elevation masks cover the nose and mouth, restricting air flow and making respiration more difficult for the athlete. They often have values that allow for adjustments to the amount of oxygen that enters the mask. The Elevation Mask 2.0 by Training Mask LLC is one type of mask that uses values and can simulate altitudes ranging from 914 m to 5486 m [2]. But the question is – do these masks really cause physiological changes in the body to improve stamina and endurance?


Figure 1. The Elevation Mask 2.0 (Training Mask LLC, Cadillac Michigan) that can be used by athletes during training in hopes of improving performance [2]. It consists of a silicone mask and neoprene head strap, with adjustable resistance caps to change the amount of air flow.


Many studies have attempted to test these masks and determine if respiratory muscle training is actually beneficial to endurance athletes. Acclimating to high altitude occurs as the body increases the amount of red blood cells, which has been shown to improve sea-level running performance [1]. However, this hematological effect has not been consistently shown in studies that used elevation training masks. In addition to the volume of red blood cells, significant changes have not been observed in blood lactate concentration in people wearing the mask during training. These trends indicate that elevation masks may work as respiratory muscle training devices but do not accurately simulate the physiological changes that occur in the body at high altitudes [2]. 

Increased aerobic capacity, or ability to pump oxygenated blood to the muscles during exercise, is one of the main goals of endurance training. By participating in any sort of endurance training program, VO2max can be improved as the body adapts to the demands being placed on it. However, the goal of altitude and respiratory muscle training is to further enhance this ability to reach peak performance levels. Studies have shown that increases in VO2max for groups wearing a mask compared to increases in control groups are not significant [2]. In contrast, ventilatory threshold, which refers to the point during exercise where the rate of ventilation increases faster than the rate of oxygen uptake, and power output show a significant increase in experimental groups wearing a mask compared to control groups [3]. These findings indicate that wearing the elevation mask may help improve the function of the cardiovascular system during exercise.

Ventilatory threshold (VT) has been shown to correlate to the amount of work the muscles can maintain without fatigue. When the VT is surpassed, the muscles do not receive the necessary amount of oxygen and fatigue begins to set in. Therefore, increasing the VT for an endurance athlete should result in better performance [4]. In addition to endurance based metrics, respiratory muscle training has been shown to improve deep breathing and increase ventilatory efficiency throughout exercise[3,5]. 

Although there seems to be trends present in studies involving elevation masks and endurance training, there are limitations to what can be concluded. Most of the studies evaluated had limited sample sizes and the duration and intensity of the exercise regimes varied between studies. However, the studies do seem to imply that elevation masks may be beneficial to endurance performance through respiratory muscle training. By making it more difficult for the athlete to inhale and exhale, the body does appear to undergo physiological changes to adapt to the lower levels of oxygen. This adaptation may result in increased VO2max, VT, and power output over time. It seems that using an elevation mask does not cause any of the hematological changes in the body that occur when a person actually reaches a higher altitude. So although endurance performance may increase as a result of using the mask, it does not directly mimic the conditions of elevation training.


Questions to Consider:

  • Prior to reading this article, had you heard of professional athletes using altitude training or elevation masks to improve their performance? And if so, what sport did these athletes participate in?
  • Do you think amateur athletes and non-athletes could benefit from using an elevation mask in daily life?
  • Have you ever experienced altitude sickness? If so, what symptoms did you have?



  1. de Paula, P., Niebauer, J. (2012). Effects of high altitude training on exercise capacity: fact or myth. Sleep Breath 16, 233–239.
  2. Porcari, J. P., Probst, L., Forrester, K., Doberstein, S., Foster, C., Cress, M. L., & Schmidt, K. (2016). Effect of Wearing the Elevation Training Mask on Aerobic Capacity, Lung Function, and Hematological Variables. Journal of sports science & medicine, 15(2), 379–386.
  3. Kido, S., Nakajima, Y., Miyasaka, T., Maeda, Y., Tanaka, T., Yu, W., Maruoka, H., & Takayanagi, K. (2013). Effects of combined training with breathing resistance and sustained physical exertion to improve endurance capacity and respiratory muscle function in healthy young adults. Journal of physical therapy science 25(5), 605–610.
  4. Graef, J.L., Smith, A.E., Kendall, K.L. et al. (2008). The relationships among endurance performance measures as estimated from VO2PEAK, ventilatory threshold, and electromyographic fatigue threshold: a relationship design. Dyn Med 7(15).
  5. Granados, J., Gillum, T., Castillo, W., Christmas, K., Kuennen, M. (2016). “Functional” Respiratory Muscle Training During Endurance Exercise Causes Modest Hypoxemia but Overall is Well Tolerated. Journal of Strength & Conditioning Research 30(3), 755-762.